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EN
The rapid growth of smart cities and industry causes an increase in waste production. The amount of municipal solid waste (MSW) increases by several factors, including population growth, economic status, and consumption trends. The inadequacy of basic trash data is a major issue for managing MSW. Numerous existing models based on solid waste prediction have been presented so far, but none of them predict solid waste accurately and also it consumes more time. To address these concerns, a deep convolutional spiking neural network for solid waste prediction (DCSNN-SWP) is proposed in this paper. Here, the real-time solid waste prediction data are gathered from the quantity of municipal corporation of Chennai (MCC), landfill, garden garbage, and coconut shell reports in Tamil Nadu (Chennai), such as Zone 9 (Nungambakkam), Zone 10 (Kodambakkam) and Zone 13 (Adyar). Then the collected solid waste data are pre-processed using the kernel correlation model. Then the pre-processing data is given to DCSNN-hybrid BCMO and Archimedes optimization algorithm which accurately predicts the solid waste as wet waste, dry waste, horticulture waste, and dumping yard for 2022-2032 years. The proposed DCSNN-SWP method has been implemented in Python.
EN
This paper describes in detail the Complex Object Generation (COG) algorithm, which is a semi-automated algorithm for the generation of instances of classes (i.e., objects) with a complex inner structure for Java and similar languages designed for black-box testing (i.e., without available source code). The algorithm was developed and tested as a stand-alone algorithm and can be used as such (e.g., during unit testing). However, we plan to use it to generate the parameter values of generated method invocations, which is a vital part of our interface-based regression testing of software components.
EN
This paper describes an algorithm for handling experimental data of periodical processes with Microsoft Excel. Thanks to this method, it is possible to prepare experimental results for analysis with the use of simple, easily available tools. The algorithm filters data and removes what is called measurement noise. This makes it possible to more precisely identify the trends in the analysed data.
PL
Opisano algorytm opracowania w Excelu danych eksperymentalnych procesów okresowych. Zaprezentowana metoda pozwala, za pomocą prostych, łatwo dostępnych narzędzi, przygotować wyniki pomiarowe do analizy. Algorytm filtruje dane, usuwając tak zwany szum pomiarowy. Dzięki temu staje się możliwe bardziej precyzyjne zauważenie trendów analizowanych danych.
EN
An effective evaluation of machines/plants condition in all cycles of their life is only possible by a cooperation between all partners (designer, producer, user, firms dealing with service/maintenance, modification, scrapping and recycling; controller for enviromental emissions and contamination). Optimising the possibilities and costs beget satisfaction of organisations/customers in accordance with ISO 9000.
PL
Mapowanie wad, czyli określenie miejsc oraz warunków dogodnych do powstawania wad zostało zaprezentowane dla walcowni walcówki. Dodatkowo wprowadzenie do analizy wariancji dokonanej na danych z biernego eksperymentu, którym były wyniki produkcji, pozwoliło określić, który z badanych czynników: gatunek czy średnica walcówki, (stopień przerobu) ma istotny wpływ na jakość. Niniejsza analiza, niezbyt kosztowna, jest dobrym narzędziem do stałej oceny pracy wydziałów, jak i większych struktur technicznych i administracyjnych w tym także realizacji zamierzeń taktyki, jak i strategii przedsiębiorstw.
EN
Mapping of defects which defines the zones and conditions convenient for occuring of defects has been presented for the wire rod mill. Variance introduced into the analysis made on data obtained in passive experiment i.e. results of production allowed to determine, which of testedfactors such as the grade or diameter of wire rod (degree of processing) have significant effect on the quality. The presented analysis is not too expensive and seems to be a useful tool for constant evaluation of production departments and larger technological and administrative structures as well as realization of companies' procedures and strategies.
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